1. Field of the Invention
The present invention relates generally to expert systems and more particularly to recognition systems.
2. Related Art
Conventional image recognition systems are not well suited to recognizing arbitrary objects. The sheer number of possible objects to be recognized, and the infinite variety of representations, relations, views and scale give rise to a multitude of intricate problems. In addition, the sources of raw image data are quite large. For example, images that may need to be analyzed by a company or government agency can be captured from various content sources including. e.g., the worldwide web (WWW), newspapers, magazines, flyers, cameras, airplanes, missiles, people, signs, buildings, maps and various video sources such as, e.g., newscasts, documentaries, camcorders, teleconferences, digital and analog video, people, and locations. A scaleable approach in terms of database size and the number of recognizable objects is needed to adequately filter and route this data.
Conventional object recognition solutions have shortcomings. The conventional solutions are geared towards recognizing specific objects of interest. The conventional solutions do not handle arbitrary images and do not easily scale to larger domains in terms of the numbers of objects they recognize.
What is needed then is a solution that provides adequate scaleability in terms of speed, accuracy, and domain size.